Artificial Intelligence from Google Environment for Effective Learning Assessment

This study investigates the use of Google NotebookLM for the automatic generation of educational assessment items. A mixed-methods approach was adopted, combining quantitative psychometric evaluation with qualitative student feedback. Six tests, each composed of 15 multiple-choice questions generated from diverse sources such as PDFs, web slides, and YouTube videos, were administered to undergraduate students. Quantitative analysis involved calculating key indices which confirmed that many AI-generated items met acceptable psychometric criteria, though some items revealed reliability concerns and potential bias. Concurrently, a structured questionnaire assessed the clarity, relevance, and fairness of the test items. Students generally rated the AI-generated questions positively in terms of clarity and pedagogical alignment, while also noting areas for improvement. In conclusion, the findings suggest that generative AI can offer a scalable and efficient solution for test item creation; however, further methodological refinements are needed to ensure consistent validity, reliability, and ethical fairness in learning assessments.